A variety of devices may perform image analysis. For example, a computer system may analyze an image to detect features of interest in the image before sending the image to a printer. Similarly, a printer may analyze an image to detect features of interest in the image before printing the image. An example of a feature of interest in an image is a boundary between objects contained in the image.
An image undergoing analysis may be represented as a two-dimensional array of pixels each having a value. An image represented as a two-dimensional array of pixels may be referred to as an image frame. An image frame may be analyzed using an image analysis window that encompasses a portion of the image frame. An image analysis window may be used to divide image analysis into successive analyses of relatively small areas of an image frame.
An analysis of an image frame may include determining whether an image analysis window contains a constant region. A constant region may be defined as a region in which all of the pixels have substantially similar values according to an analysis metric, e.g. the values are substantially similar within a predetermined tolerance. A detection of a constant region may be used, for example, to rule out the constant region as containing features of interest.
Prior methods for determining whether an image analysis window contains a constant region may include analyzing all of the pixels contained in the image analysis window. Unfortunately, analyzing all of the pixels contained in an image analysis window as the image analysis window is scanned over an image frame may be computationally intensive. For example, a 3 pixel by 3 pixel image analysis window applied to a 512 pixel wide image frame would include analyzing 9 pixels 512 times in just one 3 pixel high swath across the image frame. Large numbers of computations in detecting constant regions of an image frame slows the process of image analysis and may increase the cost of image analysis.